Application of successive projections algorithm for variable selection to determine organic acids of plum vinegar |
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Authors: | Fei Liu Yong He |
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Affiliation: | College of Biosystems Engineering and Food Science, Zhejiang University, 268 Kaixuan Road, Hangzhou, Zhejiang 310029, China |
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Abstract: | Visible and near infrared (Vis/NIR) spectroscopy was investigated to determine the acetic, tartaric and lactic acids of plum vinegar based on a newly proposed combination of successive projections algorithm-least squares-support vector machine (SPA-LS-SVM). SPA, compared with regression coefficients (RC), was applied to select effective wavelengths (EWs) with least collinearity and redundancies. Five concentration levels (100%, 80%, 60%, 40% and 20%) of plum vinegar were studied. Multiple linear regression (MLR) and partial least squares (PLS) models were developed for comparison. The results indicated that SPA-LS-SVM achieved the optimal performance for three acids comparing with full-spectrum PLS, SPA-MLR, SPA-PLS, RC-PLS and RC-LS-SVM. The root mean square error of prediction (RMSEP) was 0.3581, 0.0714 and 0.0201 for acetic, tartaric and lactic acids, respectively. The overall results indicated that Vis/NIR spectroscopy incorporated to SPA-LS-SVM could be applied as an alternative fast and accurate method for the determination of organic acids of plum vinegars. |
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Keywords: | Visible and near infrared spectroscopy Successive projections algorithm Variable selection Least squares-support vector machine Plum vinegar Organic acids |
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